Data-Type-Based Network Path Configuration

ABSTRACT

Data-type-based spanning tree reconfiguration includes determining volumes for one or more types of data transmitted in information flows in an existing spanning tree in a network. The spanning tree is reconfigured based on one or more of the volumes and the types of data transmitted in the flows.

BACKGROUND

A computer network typically comprises a plurality of interconnected nodes. A node may include end user devices, switches, servers, or other devices that transmit or receive data. Switches may include routers, bridges and other types of switches. Switches are used to efficiently transmit data in the network. Switches are in general network devices which segregate information flows over various segments of a computer network. A segment is any subset of the network computing environment including devices and their respective interconnecting communication links.

A common type of computer network is a local area network (LAN) which typically refers to a privately owned network within a single building or campus. LANs typically employ a data communication protocol, such as Ethernet, FDDI or token ring, defining the functions performed by the data link and physical layers, which are layer 1 and layer 2 in the Open Systems Interconnection (OSI) model. Multiple LANs may be connected to form a wide area network (WAN). Also, LANs may be connected to the Internet.

Most computer networks, including LANs, are either partially or fully meshed. That is, they include redundant communications paths so that a failure of any given link or node does not isolate any portion of the network. The existence of redundant links, however, may cause the formation of “loops” within the network. Loops are highly undesirable because data may traverse the loops indefinitely. Furthermore, because switches may flood, broadcast, or multicast packets, the existence of loops may cause a proliferation of data so large that the network becomes overwhelmed.

To avoid the formation of loops, most switches execute a spanning tree protocol (STP) which allows them to calculate an active network topology that is loop-free (i.e., a tree) and yet connects every node with the LAN (i.e., the tree is spanning). The Institute of Electrical and Electronics Engineers (IEEE) has promulgated the 802.1D standard that defines a spanning tree protocol to be executed by 802.1D compatible devices.

The standard spanning protocol is a naive mechanism for generating a network topology for data transmission. The spanning tree protocol is not sensitive to changing traffic in the system or types of data being transmitted. Some types of data may require particular path characteristics for transmission. For example, quality of service (QoS) sensitive applications, such as streaming video, video conferencing, voice over Internet protocol (VoIP), and graphic-intensive multiplayer games, may suffer severe degradation in quality that is unacceptable to users if path characteristics, such as one or more of bandwidth, latency, loss rate, etc., do not meet predetermined criteria. Furthermore, in large networks, it may not be feasible or cost effective for one or more system administrators to monitor the network and make decisions on assigning different paths to different information flows containing different types of data. Thus, QoS sensitive applications may suffer severe degradation in quality due to poor network path characteristics.

BRIEF DESCRIPTION OF THE DRAWINGS

Various features of the embodiments can be more fully appreciated, as the same become better understood with reference to the following detailed description of the embodiments when considered in connection with the accompanying figures, in which:

FIG. 1 illustrates a network including nodes, according to an embodiment;

FIG. 2 illustrates a spanning tree, according to an embodiment;

FIGS. 3 a-c illustrate reconfiguring a spanning tree, according to an embodiment;

FIGS. 4 a-b illustrate reconfiguring a spanning tree, according to another embodiment;

FIG. 5 illustrates a flow chart of a method for automatically reconfiguring network paths based on statistics for information flows, according to an embodiment;

FIG. 6 illustrates a flow chart of a method for calculating optimum paths for information flows in a spanning tree, according to an embodiment;

FIG. 7 illustrates a network switch, according to an embodiment; and

FIG. 8 illustrates a computer system, according to an embodiment.

DETAILED DESCRIPTION OF THE EMBODIMENTS

For simplicity and illustrative purposes, the present invention is described by referring mainly to exemplary embodiments. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments. It will be apparent however, to one of ordinary skill in the art, that the embodiments may be practiced without limitation to these specific details. Well known methods and structures may not be described in detail, so as not to unnecessarily obscure the description of the embodiments.

According to embodiments described herein, network path configuration is performed to optimize network paths based on information flows. According to an embodiment, a spanning tree is automatically reconfigured to accommodate information flows that have different types of data. The different types of data may include different content, such as different QoS sensitive applications. QoS sensitive applications include data having QoS requirements. For example, streaming media and VoIP are QoS sensitive applications, because these applications may have minimum network metric requirements for satisfactory performance, such as minimum bandwidth and maximum latency. These applications are identified and given a higher priority and may be assigned to paths that satisfy the QoS requirements for the flows, such as higher bandwidth and lower latency paths in a spanning tree. Hence, changing traffic patterns of the QoS sensitive applications in the network will automatically result in the formation of a new spanning tree that is optimized for the current types of data transmitted in the network.

An information flow, also referred to as a flow, includes information transmitted in the network. The information in a flow may be transmitted as blocks of data, and the blocks have one or more parameters in common. For example, the information is transmitted in packets in a LAN. The packets in a single flow have one or more common parameters. For example, all the packets in the flow have the same source and destination address pair.

Packets as known in the art include, in addition to payloads, embedded control and addressing information in a header that identify the source device which originated the transmission of the packet and that identify the destination device to which the packet is transmitted. Identification of source and destination devices may be by means of an address associated with each device. The addresses are referred to as the source and destination address pair and are typically provided in the packet header. An address is an identifier which is unique within the particular computing network to identify each device associated with the network. Such addresses may be unique to only a particular network environment (i.e., a network used to interconnect a single, self-contained computing environment) or may be generated and assigned to devices so as to be globally unique in co-operation with networking standards organizations. For example, the addresses may be media access control (MAC) addresses of devices in a LAN.

A source and destination address pair is one type of parameter for determining whether information belongs to a particular flow. Other parameters may also be used to determine whether information belongs to a flow.

Volume of an information flow is the amount of traffic in the flow for a period of time. This may include number of packets in a flow. Packet counts may include a count of each packet in a flow or a sample of packets. An example of a sample is incrementing a counter after a predetermined number of packets in the flow have been received. For example, a counter for a flow is incremented every 10^(th) packet. Thus, packet counts may be determined to determine the volume of an information flow. Packet counts may be performed at network switches. In most low level network communications, such as layer 2 communications in a LAN, the MAC addresses are used for routing. For each flow, packets having MAC addresses specific to the flow are counted at the switches. Using the volumes, a spanning tree is reconfigured to provide greater bandwidth to flows that have a disproportionately high volume of packets.

In addition to volume of an information flow, volume is determined for each type of data in a flow. For example, a flow may include one or more VoIP connections, streaming video, bulk transfer of data, etc. Counters may be provided for each type of data and used to determine a volume for each type of data for each flow.

Packet payloads may be parsed to determine the type of data being transmitted in the packet. For example, at a switch, bits of interest in the payload are identified and compared to signatures for the different types of data. For example, the bits of interest may include bits in predetermined locations in a packet header, such as but not limited to application header bits. The bits of interest are compared to signatures for each type of data. For example, application header bits are compared to signatures for QoS sensitive applications to determine whether any packets include data for a QoS sensitive application. If there is a match between the bits of interest in the packet and a signature, then the packet is counted to determine the volume for that type of data in that flow. This analysis is performed to determine volumes for each of the different types of data in each of the flows. The volumes may then be used to reconfigure the spanning tree.

FIG. 1 illustrates a system 100, according to an embodiment. The system 100 includes a LAN 101 comprised of nodes 110. A node is any device that may send and/or receive messages via the network and that is typically operable to perform some type of data processing. Examples of nodes include routers and other switches, servers, and end-user devices, such as personal digital assistants (PDAs), personal computers, laptops, etc.

Nodes 110 that are switches are operable to route data in the network 100 along network paths. For example, FIG. 1 shows a source node 110 x and a destination node 110 y. The source node 110 x, for example, is a server and the destination node 110 y is a client device, such as a user's personal computer (PC). A path 130 between the source node 110 x and the destination node 110 y includes links 131 a-e and intermediate nodes 110 r-u. The intermediate nodes 110 r-u may be switches routing data between the source node 110 x and the destination node 110 y.

In one embodiment, the switches in the LAN 101 are organized as a spanning tree. As is known in the art, a spanning tree, for example, generated using the 802.1D spanning tree protocol (STP) is a loopless configuration including a root node and paths between the nodes in the tree. As a consequence of running STP, a single path may be provided from source to destination. The node 110 r, for example, is the root node and the other switches in the LAN 101 are leaves in the spanning tree. The switches in the LAN 101 may be layer 2 devices that route packets in the paths in the spanning tree using the packets' MAC addresses. For example, each switch may include multiple incoming and outgoing ports. Each switch may also include a table of MAC addresses and associated ports for the MAC address. When a packet arrives on an incoming port, a table lookup may be performed to identify the corresponding outgoing port to route the packet along a path in the spanning tree. The path 130, for example, represents a path in the spanning tree. The path 130 includes links 131 a-e. The switches 110 r-u route packets along the path 130 using MAC address-port relationships stored in their tables. FIG. 2 illustrates paths and flows in a spanning tree, which is described in detail below.

The LAN 101 may be connected to other LANs, such as the LAN 111, and/or the Internet. Edge routers, such as nodes 110 g and 110 h, may provide gateways to other LANs, the Internet, or other networks.

It will be apparent to one of ordinary skill in the art that the system 100 and the LAN 101 are examples of systems and networks that the embodiments described herein may be practiced. The embodiments described herein may be practiced in other systems and networks as well.

FIG. 2 illustrates a spanning tree 200. The node 110 r is the root node and the other nodes, 110 s-u and 110 a-e, are also in the spanning tree. All the nodes in a network may be included in a spanning tree and the spanning tree 200 may be considered a partial topology for all the nodes 110 in the LAN 101 shown in FIG. 1.

FIG. 2 shows physical connections between the nodes, which may include wired connections between the nodes. Also, shown are paths in the spanning tree 200. Flows travel along the paths. For example, the flow 131 follows the path through the nodes 110 b, 110 a, and 110 r-t. Another flow 132 follows the path through the nodes 110 b, 110 a, and 110 r-u. Other flows follow other shown paths. Each flow may include packets, however, some networks may transmit non-packetized data. In one example for determining flows, packets with the same source and destination pair are provided in a flow. Each flow may include different types of data. For example, the flow 131 may carry VoIP data and streaming video between the same source and destination. The flow 132 may include two different VoIP connections. As shown, the flow 131 between the source node 110 b and the destination node 110 t includes at least VoIP data. As shown, the flow 132 between the source node 110 b and the destination node 110 u also includes at least VoIP data.

The nodes shown in FIG. 2 may be switches, and the switches may determine volumes for each flow and for each type of data in each flow. For example, the packets are analyzed to determine whether the packets include one of the different types of data. This may include determining whether packets include data for one of a plurality of different QoS sensitive applications. Packet counts are performed for packets carrying the different types of data. A packet count for each type of data may be determined as used as the volume for that type of data and stored at each switch. Also, packets counts for an entire flow may be determined and stored at each switch. In addition to packet counts, other information about a flow may be stored, such as type of data, flow identifier, priority tag for each type of data, etc.

FIG. 3 a illustrates the nodes 110 r-u and 110 a-e determining flow statistics. The nodes 110 s-u and 110 a-e send the flow statistics 301 to the root node 110 r. The flow statistics include volume of data transmitted in each information flow for each type of data. The flow statistics 301 may include other information also.

For example, upon start-up, each switch, such as each of nodes 110 r-u and 110 a-e, broadcasts a message containing its ID. The switches may use IDs that are larger than the largest valid host address for that subnet so there is no conflict between hosts, which have lower-value IDs, and switches, which have higher-valued IDs. Then, a spanning tree is generated and each node sends a message containing its set of neighbors, i.e., the adjacency list, to the current root node in the resulting spanning tree. As soon as the designated ports are assigned and the data paths for switching are functional in the spanning tree, each switch/router enables volume determination for flows. For example, each switch/router enables counting of packets between each source and destination pairs and for each type of data by incrementing relevant counters.

In one embodiment, a counter is provided for each type of data, and a counter for the type of data is selected by hashing a value, such as hashing a source and destination pair and bits of interest. Then, the selected counter is incremented. Count values may be incremented based on packets received at an ingress port or packets being transmitted on an outbound port. The volumes, which may include the counter values, are transmitted to the root node as flow statistics, such as shown in FIG. 3 a by the flow statistics 301 being transmitted to the root node 110 r.

In FIG. 3 b, the root node 110 r reconfigures the spanning tree by calculating optimal paths based on the flow statistics 301 and flow statistics captured at the root node 110 r. The reconfigured spanning tree may include a new root node and new paths. The root node 110 r sends update messages 302 to the nodes 110 s-u and 110 a-e for configuring the new spanning tree. The update messages 302 include information for each node to reconfigure the spanning tree, such as identification of the new root node and a new adjacency list for each node. The new adjacency list is used to determine which neighbors to exclude in the new spanning tree, and is used by each node to block and unblock ports that result in the reconfiguration of the spanning tree. Also, a message is sent to the new root from the current root handing over control to the new root, so the new root knows that it is needs to function as the new root.

FIG. 3 c shows a topology of the new spanning tree 310. For example, the new root node is the node 110 s. The flow 131 now has a shorter path. For example, the flow 131 may include a high-priority QoS sensitive application having a disproportionately high volume when compared to the other types of data. Thus, the flow 131 is given a shorter path in the reconfigured spanning tree 310. Other flows may have the same or different paths based on the flow statistics considered when calculating the new paths. The flow 132 is also assigned to a shorter path, because the flow 132 may have high volume and/or the flow 132 includes a QoS sensitive application.

FIGS. 4 a-b are similar to FIGS. 3 a-b except flow statistics are sent to a node that is not the root node. For example, the computer system 400 receives the flow statistics 300 and reconfigures the spanning tree. The computer system calculates optimum paths based on the flow statistics and sends the update messages 302 to the nodes, as shown in FIG. 4 b. The new spanning tree 310 is created and shown in FIG. 3 c. Thus, a node other than a root node may reconfigure the spanning tree. The node, for example, is a computer system operable to communicate with the switches and other nodes in the network to reconfigure and implement a new spanning tree.

FIG. 5 illustrates a flow chart of a method 500 for automatically reconfiguring network paths based on flow statistics for information flows, according to an embodiment. The method 500 is described with respect to one or more of FIGS. 1-4 c by way of example and not limitation.

At step 501, flow statistics are determined for information flows traveling along existing network paths. The flow statistics include volume for each type of data in each information flow. The flow statistics may also identify the types of data be transmitted in the flows and possibly other parameters about the flows.

For example, the spanning tree 200 includes flows 131 and 132 shown in FIG. 2. Switches in the paths may determine the flow volumes for different types of data. For example, the nodes 110 r-u determine the volume for VoIP data in the flow 131 by parsing the header of each received packet to identify a source and destination address pair to identify the flow and by parsing the packet payload to determine whether the packet includes VoIP data. The different types of data may include different types of content, such as one or more QoS sensitive applications. Data analysis may include deep packet inspection. For example, the payload of the packet is inspected to determine whether the payload includes one of the types of data. Payload inspection may include comparing bits of interest in the payload to signatures for the different types of data. A signature may include one or more bits that can be used to identify a particular type of data, such as application header bits or other bits that may be unique to a particular type of data. When a packet is identified as including one of the types of data, a counter for that type of data is incremented. A counter may be provided for each type of data. The volumes for each type of data may include the packet counts. Other flow statistics may also be determined and stored at each node, and transmitted to a node for reconfiguring the spanning tree. Flow volumes for all the data in a flow may also be determined.

At step 502, the spanning tree is reconfigured based on the flow statistics. In one embodiment, spanning tree is reconfigured based on the flow volumes to provide the higher-volume information flows with shorter paths in the reconfigured spanning tree. This may include reconfiguring the spanning tree based on the flow volumes for each type of data. For example, the root node 110 r shown in FIGS. 3 a-b or the computer system 400 shown in FIGS. 4 a-b receives the flow statistics 301 and reconfigures the spanning tree based on the flow statistics. As shown in FIG. 3 c, the flow 131 is given a shorter path, for example, because it has a higher volume than the other flows. Other flow statistics may also be considered when reconfiguring the spanning tree. For example, the different types of data may be prioritized. For example, a priority tag is stored with the volume for each type of data and indicates the priority for that type of data. The priorities may be predetermined. Flows carrying QoS sensitive applications may be given higher priorities and assigned to higher bandwidth and lower latency paths such that the QoS requirements for the data are satisfied. For example, streaming video or VoIP data may have a predetermined maximum latency. If the maximum latency is exceeded, the streaming video or VoIP connection may be degraded beyond user satisfaction. Thus, the streaming video or VoIP connection is assigned to a lower latency path in the spanning tree.

The method 500 may be invoked if any flow volumes are disproportionately high or may be invoked at predetermined intervals. For example, if the number of packets for a flow exceeds a threshold as determined at a switch, such as one of the nodes 110 r-u or 110 a-e shown in FIGS. 2, 3 a-b and 4 a-b, the node sends flow statistics to the node operable to reconfigure the spanning tree, such as the root node 110 r or the computer system 400. That node may request and receive flow statistics from all the other switches in the spanning tree, and reconfigure the spanning tree based on the flow statistics. The flow with the packet count exceeding the threshold may be assigned to a path with greater bandwidth.

A node, such as the root node 110 r or the computer system 400, may also invoke the reconfiguration. For example, the root node 110 r or the computer system 400 requests the node to send flow statistics captured during a predetermined interval. The root node 110 r or the computer system 400 may request that each node sends its flow statistics at different times to avoid flooding the network and the receiving node and to avoid data collisions. The root node 110 r or the computer system 400 then reconfigures the spanning tree based on the flow statistics.

FIG. 6 illustrates a method 600, according to an embodiment, for calculating optimum paths for information flows in a spanning tree. The steps of the method 600 may be sub-steps of the step 502 of the method 500 for reconfiguring the spanning tree. The method 600 is described with respect to one or more of FIGS. 1-4 c by way of example and not limitation.

At step 601, the flows are prioritized based on one or more of the flow statistics determined at step 501 in the method 500. For example, the flows are prioritized based on the flow volumes for each type of data and predetermined priorities for the different types of data. Higher flow volumes are given a higher priority so they are assigned to shortest paths at step 602.

Multiple flow statistics may be used to prioritize flows. For example, flows may be first prioritized based on the type of data in the flows. For example, the flow 131 shown in FIG. 2 carries VoIP data and streaming video. The VoIP may be given a higher priority over the streaming video because it requires lower latency and the users demand high-quality VoIP connections for their business telephone lines. The priorities for VoIP and streaming video may be predetermined. Priority tags may be stored with the data to indicate its priority. For example, VoIP has the highest priority and is given a priority tag of “1”; streaming video is given a priority tag of “2”; and so on. Within the first prioritization, the flows are again prioritized based on the volumes for each type of data in each flow. For example, flows having VoIP data are further prioritized based on their flow volumes. Streaming video, for example, is given the second highest priority and flows having streaming video are further prioritized based on their flow volumes. Other flow statistics may also be used to prioritize flows.

At step 602, the spanning tree is reconfigured based on the priorities determined at step 601. In one embodiment, an edge graph is created and flows are assigned to shortest paths based on priority. For example, the root node 110 r or the computer system 400 stores a graph in adjacency list representation and flow characteristics, such as packet counts for each source and destination pair and type of data. Adjacency list representation includes a list of adjacent nodes for each node, which is determined using, for example, the 802.1D STP. The list of flows is sorted based on corresponding packet counts and data type, if data type was used to prioritize. The edge graph is a set of vertices, which are nodes in paths, and links connecting the nodes, which are the edges. Associate with each flow, starting with the highest priority flow, the edge set corresponding to the shortest path between the source and destination. The edge set is the set of links forming the shortest path. Starting from an empty graph, put in edges from the shortest paths of each flow in priority order such that it does not form a cycle, and then repeat until all the source and destination pairs are connected in the graph via edges. A shortest path is based on a network metric or a combination of network metrics, such as bandwidth, latency, etc. For example, a lowest latency path and/or a highest bandwidth path may be the shortest path. A known function, such as the red-blue rule in matroid theory or another known function may be used to build the edge graph. However, the known function uses as input the priorities determined based on the flow statistics to assign paths in the spanning tree to flows.

This method assigns flows to optimum paths in a spanning tree based on flow statistics. Determining which path is optimum for a particular flow may be based on predetermined flow statistics. In the example described above, QoS requirements for types of data in a flow and flow volumes are the predetermined flow statistics for prioritizing flows and assigning optimum paths based on the priority. An optimum path may be a shortest path in the network, where shortness of a path is based on one or more network metrics. For example, the reconfiguration results in a spanning tree that assigns highest priority flows to the shortest paths, which are likely paths with the greatest bandwidth and/or lowest latency. Furthermore, this method for assigning flows to paths minimizes the number of detour packets (packets not on the shortest path from the source to the destination), and thus achieves load sharing and minimizes delay for most packets. Furthermore, based on the flow statistics used to prioritize the flows, the spanning tree may be reconfigured to best satisfy an objective other than load sharing.

FIG. 7 illustrates a block diagram of switch 700 that may be used for some of the nodes in the LAN 101, such as many of the nodes shown in FIGS. 1-4 c. FIG. 7 is a high-level, generic block diagram of a switch, and the switch may include many conventional elements not shown.

The switch 700 includes one or more control processors 701 for performing routing in the switch and other known functions. The switch 700 also includes multiple line cards 702. Each line card includes ports 703, switching hardware/slave processor 704, and a flow counter 705 for counting packets for each flow. The control processors 701 may include memory 706 storing tables and storing software performing one or more of the steps described herein. These may include but are not limited to steps for determining flow volumes and other flow statistics and steps for reconfiguring the spanning tree. Also, hardware or a combination of hardware and software in the switch 700 may perform one or more of the steps described herein. The tables may include flow statistics, such as identifiers identifying each flow, flow volumes and volumes for each type of data in each flow, priority tags for each type of data and for each volume for each type of data, network path measurements, such as number of hops, bandwidth, latency, etc., and other information. The flow statistics may be transmitted to a root node or another node for reconfiguring the spanning tree as described above. The software stored in memory in the switch 700 may include but is not limited to steps for determining flow volumes and other flow statistics and steps for reconfiguring the spanning tree, which may include one or more of the steps described with respect to methods 500 and 600. Also, hardware or a combination of hardware and software in the switch 700 may perform one or more of the steps described herein.

FIG. 8 illustrates a block diagram of the computer system 400 shown in FIGS. 4 a-b. The computer system 800 includes one or more processors, such as processor 802, providing an execution platform for executing software. Commands and data from the processor 802 are communicated over a communication bus 805. The computer system 800 also includes a main memory 808, such as a Random Access Memory (RAM), where software may be resident during runtime, and a secondary memory 806. The secondary memory 806 includes, for example, a hard disk drive and/or a removable storage drive, representing a floppy diskette drive, a magnetic tape drive, a compact disk drive, etc., or a nonvolatile memory where a copy of the software may be stored. The secondary memory 806 may also include ROM (read only memory), EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM). In addition to software for routing and other steps described herein, routing tables, capacities for overlay paths, available bandwidths for overlay paths, and other data may be stored in the main memory 808 and/or the secondary memory 806. The memories 808 and/or 806 may store network metric measurements, including feature vectors and measured available bandwidths.

A user interfaces with the computer system 800 with one or more I/O devices 807, such as a keyboard, a mouse, a stylus, display, and the like. A network interface 816 is provided for communicating with other nodes in the network 100.

One or more of the steps of the methods 500 and 600 and other steps described herein may be implemented as software, hardware or a combination of hardware and software. Software is embedded on a computer readable medium, such as memory and executed, for example, by a processor. The steps may be embodied by a computer program, which may exist in a variety of forms both active and inactive. For example, they may exist as software program(s) comprised of program instructions in source code, object code, executable code or other formats for performing some of the steps. Any of the above may be embodied on a computer readable medium, which include storage devices and signals, in compressed or uncompressed form. Examples of suitable computer readable storage devices include conventional computer system RAM (random access memory), ROM (read only memory), EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM), and magnetic or optical disks or tapes. Examples of computer readable signals, whether modulated using a carrier or not, are signals that a computer system hosting or running the computer program may be configured to access, including signals downloaded through the Internet or other networks. Concrete examples of the foregoing include distribution of the programs on a CD ROM or via Internet download. In a sense, the Internet itself, as an abstract entity, is a computer readable medium. The same is true of computer networks in general. It is therefore to be understood that those functions enumerated below may be performed by any electronic device capable of executing the above-described functions.

While the embodiments have been described with reference to examples, those skilled in the art will be able to make various modifications to the described embodiments without departing from the scope of the claimed embodiments. 

1. A method of data-type-based spanning tree reconfiguration in a network, the method comprising: identifying at least one type of data transmitted in information flows in a spanning tree in the network; determining a volume of data transmitted in each information flow for each type of data; and reconfiguring the spanning tree based on the volumes.
 2. The method of claim 1, wherein the at least one type of data comprises a plurality of different types of data transmitted in the information flows and determining a volume of data comprises: analyzing the data transmitted in the information flows to determine whether the data includes one of the different types of data; and determining the volumes for the different types of data based on the analysis.
 3. The method of claim 2, wherein the data transmitted in the information flows is transmitted in packets and analyzing the data comprises: identifying bits of interest in a payload of each packet; comparing the bits of interest to signatures for the different types of data; and determining the payload to include the one of the different types of data if the bits of interest matches the signature for the one of the different types of data.
 4. The method of claim 3, wherein determining the volumes for the different types of data comprises: determining a packet count for each of the different types of data based on the comparison of the bits of interest to signatures for the different types of data.
 5. The method of claim 3, wherein a different counter is provided for each type of data and determining a packet count for each of the different types of data comprises: incrementing the counter for the one of the different types of data if the bits of interest matches the signature for the one of the different types of data.
 6. The method of claim 5, wherein each information flow comprises packets transmitted on a path in the spanning tree from a particular source to a particular destination, and each information flow has a different source and destination pair and incrementing the counter comprises: selecting the counter for the one of the different types of data by hashing a tuple comprised of the source address, destination address and the bits of interest in the packet.
 7. The method of claim 5, wherein the counters comprise bloom filter counters.
 8. The method of claim 3, wherein the different types of data comprise a plurality of different QoS sensitive applications.
 9. The method of claim 8, wherein the bits of interest comprise bits in an application header in the payload of the packet.
 10. The method of claim 1, further comprising: prioritizing the information flows based on the volumes for each information flow; and the reconfiguring comprises reconfiguring the spanning tree based on the priorities.
 11. The method of claim 10, further comprising: assigning a predetermined priority associated with each type of data with the volume for each type of data; prioritizing the information flows additionally based on the priority for each data type; and the reconfiguring comprises reconfiguring the spanning tree based on the assigned predetermined priorities.
 12. The method of claim 1, further comprising: determining whether any of the volumes exceeds a threshold; and if any of the volumes exceed the threshold, performing the reconfiguring of the spanning tree.
 13. The method of claim 1, wherein determining a volume of data transmitted in each information flow for each type of data comprises: receiving the volumes, wherein the volumes include volumes of data transmitted in the information flows for each type of data and the volumes are captured during one or more predetermined time intervals.
 14. The method of claim 1, wherein determining a volume of data transmitted in each information flow for each type of data comprises: determining a number of packets transmitted in each information flow; and determining a number of packets for each type of data transmitted in each information flow.
 15. The method of claim 1, wherein the network comprises a local area network and switches in the local area network determine the volumes of data for the information flows.
 16. A computer program embedded on a computer readable storage medium, the computer program including instructions that when executed by a processor implement a method of data-type-based spanning tree reconfiguration in a network, the method comprising: determining flow statistics for information flows in an existing spanning tree in the network, the flow statistics including volumes of data transmitted in each information flow for at least one type of data; and determining optimum paths for a new spanning tree based on the flow statistics.
 17. The computer program of claim 16, wherein the at least one type of data comprises a plurality of different types of data and the method further comprises: analyzing the data transmitted in the information flows to determine whether the data includes one of the different types of data; and determining the volumes for the different types of data based on the analysis.
 18. The computer program of claim 17, wherein the data transmitted in the information flows is transmitted in packets and analyzing the data comprises: identifying bits of interest in a payload of each packet; comparing the bits of interest to signatures for the different types of data; and determining the payload to include the one of the different types of data if the bits of interest matches the signature for the one of the different types of data.
 19. The computer program of claim 16, wherein determining optimum paths for a new spanning tree further comprises: prioritizing the information flows based on the volumes for the at least one type of data in each information flow; and the determining optimum paths comprises determining the optimum paths based on the priorities.
 20. A node in a network comprising: memory storing flow statistics for information flows in an existing spanning tree in the network, the flow statistics including a volume of data transmitted in each information flow for at least one type of data; and a processor determining optimum paths for a new spanning tree based on the flow statistics. 